• KernSmooth

  • Referenced in 1018 articles [sw04586]
  • sets without the imposition of a parametric model. The main goal of this book...
  • survival

  • Referenced in 201 articles [sw04364]
  • descriptive statistics, two-sample tests, parametric accelerated failure models, Cox model. Delayed entry (truncation) allowed ... models; interval censoring for parametric models. Case-cohort designs...
  • bootlib

  • Referenced in 461 articles [sw40642]
  • with single samples from parametric and nonparametric models. Chapter 3 extends the basic ideas...
  • System Identification Toolbox

  • Referenced in 179 articles [sw05686]
  • supported. These include the use of non-parametric, subspace-based, and prediction-error algorithms coupled ... either MIMO state space or MISO polynomial model structures. A key feature of the software ... models, the use of non-standard model parametrizations, and the employment of Expectation Maximization...
  • GMRFLib

  • Referenced in 338 articles [sw06641]
  • data, spatio-temporal models, graphical models, and semi-parametric statistics. With so many applications ... GMRFs in complex hierarchical models, in which statistical inference is only possible using Markov Chain...
  • np

  • Referenced in 103 articles [sw10543]
  • specification tests for parametric mean regression models and parametric quantile regression models, among others...
  • quantreg

  • Referenced in 162 articles [sw04356]
  • nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate...
  • Church

  • Referenced in 55 articles [sw08946]
  • processes. Church is based on the Lisp model of lambda calculus, containing a pure Lisp ... simple description of many complex non-parametric models. We illustrate language features through several examples ... planning by inference, and various non-parametric clustering models. Finally, we show how to implement...
  • SemiPar

  • Referenced in 761 articles [sw07116]
  • viewed as a relatively simple extension of parametric regression and treat the two together. They ... based on penalized regression splines and mixed models. Every model in this book...
  • CONTSID

  • Referenced in 37 articles [sw14945]
  • testing and evaluating these data-based modelling techniques. The CONTSID toolbox was first released ... identifying linear dynamic continuous-time parametric models from measured input/output sampled data; it provides transfer...
  • multcomp

  • Referenced in 36 articles [sw10485]
  • intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects...
  • BEEM

  • Referenced in 30 articles [sw09815]
  • benchmark set includes more than 50 parametrized models (300 concrete instances) together with their correctness...
  • frailtypack

  • Referenced in 44 articles [sw06070]
  • frailtypack: General Frailty models using a semi_parametric penalized likelihood estimation or a parametric estimation ... also a parametric estimation. 1) A shared gamma frailty model and Cox proportional hazard model...
  • party

  • Referenced in 28 articles [sw07330]
  • regression models into a well defined theory of conditional inference procedures. This non-parametric class ... algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression...
  • flexsurv

  • Referenced in 20 articles [sw15470]
  • Survival and Multi-State Models. Flexible parametric models for time-to-event data, including ... Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution ... fitting and predicting from fully parametric multi-state models...
  • DPpackage

  • Referenced in 72 articles [sw10495]
  • requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against...
  • spdep

  • Referenced in 39 articles [sw04578]
  • unweighted SAR and CAR spatial regression models, semi-parametric and Moran eigenvector spatial filtering...
  • MatchIt

  • Referenced in 17 articles [sw10538]
  • King, and Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching ... hard-to-justify, but commonly made, statistical modeling assumptions. The software also easily fits into ... with MatchIt, researchers can use whatever parametric model they would have used without MatchIt...
  • lmtest

  • Referenced in 19 articles [sw04478]
  • some generic tools for inference in parametric models are provided...
  • Rhinoceros

  • Referenced in 19 articles [sw07518]
  • toolpath generation directly in Rhino. Like many modeling applications, Rhino also features a scripting language ... avant-garde architects are using parametric modeling tools, like Grasshopper. Rhino’s increasing popularity...